Instructions to use kinzakhan1/SRD_V7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- Unsloth Studio new
How to use kinzakhan1/SRD_V7 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kinzakhan1/SRD_V7 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kinzakhan1/SRD_V7 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for kinzakhan1/SRD_V7 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="kinzakhan1/SRD_V7", max_seq_length=2048, )
SRD_V7 - Standard Reasoning (SRD) Model (V7)
Dataset
- Source: CoT_reasoning_unsloth.jsonl
- Examples: 9,340
- Format: messages[] chat format
Training Configuration
| Parameter | Value |
|---|---|
| Learning Rate | 0.00015 |
| LoRA Rank | 32 |
| LoRA Alpha | 64 |
| LoRA Dropout | 0.0 |
| Target Modules | All (MLP + Attention) |
| Epochs | 2 |
| Batch Size (effective) | 16 |
| Warmup | 3% |
| RSLoRA | Disabled |
Training Results
- Training Time: 1.38 hours
- Final Loss: 1.2049
Part of Experiment
- kinzakhan1/CRD_V7
- kinzakhan1/SRD_V7 (this model)
- kinzakhan1/MIXED_V7
- Downloads last month
- 2
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